Introduction to Data Analytics with KNIME

Video description

This is a hands-on basic course about data analytics and KNIME, and is designed for learners with little experience in data analytics or in programming. Taught by 24 year data analytics veteran Dr. Rosaria Silipo, it covers everything a beginning data analyst needs to know. You'll learn about importing data from common data sources and how to investigate data using visual exploration, ETL, data blending, and some machine learning algorithms.

You'll explore prediction models, clustering models, recommendation models, PMML models, and how to build a report in BIRT and the KNIME WebPortal. By course end, you'll possess a basic understanding of the methods of data analytics as well as practical skills in using the KNIME platform for your own purposes.

  • Learn the basics of data analytics and how to apply them in real life scenarios using KNIME
  • Understand what the KNIME data analytics platform is and what it can do
  • See how beginners without programming skills can use KNIME for data analytics
  • Gain experience installing and working with the KNIME platform
  • Enjoy access to sample data analytics workflows and exercises
Dr. Rosaria Silipo has been working in data analytics since 1992. She is a principal data scientist for AG. She's held senior positions with Siemens, Viseca AG, and Nuance Communications; she holds a PhD in Bioengineering from the Politecnico di Milano and a Masters in Electrical Engineering from the University of Florence; and is the author of more than 50 scientific publications, many scientific whitepapers, and a number of books for data science practitioners.

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Table of contents

  1. Introduction
    1. Welcome To The Course 00:01:10
    2. About The Author 00:01:41
  2. Introduction To The KNIME Analytics Platform
    1. What Is The KNIME Analytics Platform And What It Can Do For You 00:04:15
    2. Installation Of The KNIME Analytics Platform 00:03:31
    3. A Quick Tour Of The KNIME Analytics Platform 00:05:34
    4. Available Resources And Preview Of Final Goals For This Course 00:04:19
    5. GUI Based Programming: Workflows, Nodes, And Importing Workflows 00:03:18
  3. Data Access
    1. Reading From A Text File 00:06:50
    2. Database Access 00:07:01
    3. External REST Services 00:04:17
    4. Artificial Data Generation 00:04:12
    5. Other Data Access Nodes 00:03:00
    6. Exercise 00:00:48
  4. Data Visualization
    1. Data Visualization 00:03:25
    2. JavaScript Based Visualization 00:06:54
    3. Data Views 00:05:32
    4. Highlighting 00:04:20
    5. Graphics Through R 00:03:21
    6. Exercise 00:01:06
  5. ETL And Data Manipulation
    1. Data Filtering 00:06:07
    2. Data Aggregations 00:06:21
    3. Concatenation And Join 00:05:29
    4. Data Transformations 00:07:53
    5. Workflow Clean Up 00:04:39
    6. Datetime Manipulation 00:06:20
    7. In-Database Processing 00:06:21
    8. Exercise 00:00:45
  6. Data Mining
    1. Process Overview 00:04:53
    2. Training And Applying A Decision Tree 00:05:40
    3. Scoring A Model 00:06:21
    4. PMML 00:04:45
    5. K-Means Clustering 00:05:21
    6. Recommendation Engines 00:06:33
    7. Other Models Available 00:06:27
    8. Exercise 00:00:47
  7. Reporting
    1. Reporting Overview 00:02:12
    2. BIRT Integration 00:04:55
    3. Other Commercial Integrations 00:04:07
    4. KNIME WebPortal 00:06:22
    5. Exercise 00:00:55
  8. Conclusion
    1. Wrap Up And Thank You 00:02:28

Product information

  • Title: Introduction to Data Analytics with KNIME
  • Author(s): Rosaria Silipo
  • Release date: September 2016
  • Publisher(s): Infinite Skills
  • ISBN: 9781491967539